Student Perspectives on Teacher Interpersonal Behaviours in AI-Mediated Higher Education: A Q Methodology Study

Research on artificial intelligence (AI) in higher education largely emphasises technical performance and outcomes, leaving student views of teacher interpersonal behaviours in AI-mediated classrooms insufficiently understood. In response, this study applied Q methodology, supported by content and sentiment analyses, to examine student perspectives. A total of 30 university students Q-sorted 40 statements, covering empathy, immediacy, clarity, autonomy support, engagement and personalization. Subsequently, principal component analysis with varimax rotation yielded four factors: (F0) Selective-Connection Seekers, (F1) Autonomous Collaborators, (F2) Gamification-Driven Minimalists and (F3) Clarity and Empathy Advocates. Additionally, open-ended reflections clustered into seven themes, with Clarity and Instructional Precision and Empathy and Emotional Support most frequent. At the same time, sentiment analysis showed predominantly positive–neutral tones, with some resistance to over-personalization. Overall, the findings indicated that authentic interaction, transparent criteria and profile-aligned differentiation (including targeted gamification) are pivotal for sustaining meaningful teacher–student relationships. Accordingly, several actionable suggestions were provided based on the findings.